Contact Dr Iveta Eimontaite
Areas of expertise
- Industrial Automation
- Industrial Ergonomics and Human Factors
Iveta Eimontaite studied Cognitive Neuroscience (MSc, University of York, UK) and completed her PhD in Cognitive Psychology (Hull University, UK). Prior to joining Cranfield University in June 2019, Iveta held research positions at Bristol Robotics Laboratory (at the University of West of England) and Sheffield Robotics (at the University of Sheffield). Her work mainly focuses on behavioural and cognitive aspects of Human-Technology Interaction (HTI) with particular interest in user needs and requirements for the successful integration of technology within the workplace/social environments.
Within SATM’s Industrial Psychology and Human Factors group (IPHF) Iveta works on the H2020 project SHERLOCK (http://www.sherlock-project.eu/). Her role within this project focuses on acceptance and wellbeing of operators in manufacturing who are working collaboratively with high payload robotic arms, exoskeletons and mobile manipulators in diverse production environments. Iveta is employing a range of qualitative and quantitative methods in conjunction with physiological measures to estimate key psychological safety factors and ensure operator engagement and wellbeing.
Articles In Journals
- Cameron D, Collins EC, de Saille S, Eimontaite I, Greenwood A & Law J (2023) The social triad model: considering the deployer in a novel approach to trust in human–robot interaction, International Journal of Social Robotics, Available online 13 September 2023.
- Eimontaite I, Cameron D, Rolph J, Mokaram S, Aitken JM, Gwilt I & Law J (2022) Dynamic graphical instructions result in improved attitudes and decreased task completion time in human–robot co-working: an experimental manufacturing study, Sustainability, 14 (6) Article No. 3289. Dataset/s: 10.6084/ m9.figshare.19328717
- Ariansyah D, Erkoyuncu JA, Eimontaite I, Johnson T, Oostveen A-M, Fletcher S & Sharples S (2022) A head mounted augmented reality design practice for maintenance assembly: toward meeting perceptual and cognitive needs of AR users, Applied Ergonomics, 98 (January) Article No. 103597. Dataset/s: 10.17862/cranfield.rd.15195594.v1
- Leesakul N, Oostveen A-M, Eimontaite I, Wilson ML & Hyde R (2022) Workplace 4.0: exploring the implications of technology adoption in digital manufacturing on a sustainable workforce, Sustainability, 14 (6) Article No. 3311.
- Ibarguren A, Eimontaite I, Outon JL & Fletcher S (2020) Dual arm co-manipulation architecture with enhanced human–robot communication for large part manipulation, Sensors, 20 (21) Article No. 6151.
- Eimontaite I, Gwilt I, Cameron D, Aitken JM, Rolph J, Mokaram S & Law J (2018) Language-free graphical signage improves human performance and reduces anxiety when working collaboratively with robots, The International Journal of Advanced Manufacturing Technology, 100 55-73. Dataset/s: 10.1007/s00170-018-2625-2
- Sun Y, She S, Yang F, Ashworth P, Eimontaite I & Wang J (2017) Critical factors and pathways influencing genetically modified food risk perceptions, Journal of Risk Research, 22 (1) 44-54. Dataset/s: 10.1080/13669877.2017.1351468
- Eimontaite I, Nicolle A, Schindler I & Goel V (2013) The effect of partner-directed emotion in social exchange decision-making, Frontiers in Psychology, 4, Article No. 469. Dataset/s: 10.3389/fpsyg.2013.00469
- Fletcher S, Eimontaite I, Webb P & Lohse N (2023) “We don’t need ergonomics anymore, we need psychology!” – The human analysis needed for human-robot collaboration. In: 14th International Conference on Applied Human Factors and Ergonomics 2023, and Affiliated Conferences, San Francisco, 20-24 July 2023.
- Eimontaite I, Voinescu A, Alford C, Caleb-Solly P & Morgan P (2020) The impact of different human-machine interface feedback modalities on older participants' user experience of CAVs in a simulator environment. In: Advances in Human Factors of Transportation, Washington DC, 24-28 July 2019.